Knowledge Gaps in Generating Cell-Based Drug Delivery Systems and a Possible Meeting with Artificial Intelligence
- Negin Mozafari
Negin MozafariDepartment of Pharmaceutics, School of Pharmacy, Shiraz University of Medical Sciences, 71468 64685 Shiraz, IranMore by Negin Mozafari
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- Niloofar Mozafari
Niloofar MozafariDesign and System Operations Department, Regional Information Center for Science and Technology, 71946 94171 Shiraz, IranMore by Niloofar Mozafari
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- Ali Dehshahri*
Ali Dehshahri*Email: [email protected]. Fax/Phone: +987132424126 (ext. 251).Department of Pharmaceutical Biotechnology, School of Pharmacy, Shiraz University of Medical Sciences, 71468 64685 Shiraz, IranPharmaceutical Sciences Research Centre, Shiraz University of Medical Sciences, 71468 64685 Shiraz, IranMore by Ali Dehshahri
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- Amir Azadi*
Amir Azadi*Email: [email protected]. Fax/Phone: +987132424126 (ext. 202).Department of Pharmaceutics, School of Pharmacy, Shiraz University of Medical Sciences, 71468 64685 Shiraz, IranPharmaceutical Sciences Research Centre, Shiraz University of Medical Sciences, 71468 64685 Shiraz, IranMore by Amir Azadi
Abstract
Cell-based drug delivery systems are new strategies in targeted delivery in which cells or cell-membrane-derived systems are used as carriers and release their cargo in a controlled manner. Recently, great attention has been directed to cells as carrier systems for treating several diseases. There are various challenges in the development of cell-based drug delivery systems. The prediction of the properties of these platforms is a prerequisite step in their development to reduce undesirable effects. Integrating nanotechnology and artificial intelligence leads to more innovative technologies. Artificial intelligence quickly mines data and makes decisions more quickly and accurately. Machine learning as a subset of the broader artificial intelligence has been used in nanomedicine to design safer nanomaterials. Here, how challenges of developing cell-based drug delivery systems can be solved with potential predictive models of artificial intelligence and machine learning is portrayed. The most famous cell-based drug delivery systems and their challenges are described. Last but not least, artificial intelligence and most of its types used in nanomedicine are highlighted. The present Review has shown the challenges of developing cells or their derivatives as carriers and how they can be used with potential predictive models of artificial intelligence and machine learning.
Cited By
This article is cited by 1 publications.
- Negin Mozafari, Sheida Jahanbekam, Hajar Ashrafi, Mohammad-Ali Shahbazi, Amir Azadi. Recent Biomaterial-Assisted Approaches for Immunotherapeutic Inhibition of Cancer Recurrence. ACS Biomaterials Science & Engineering 2024, 10 (3) , 1207-1234. https://doi.org/10.1021/acsbiomaterials.3c01347